The penetration of solar energy into centralized electric grids has increased significantly during the last decade. Although the electricity from photovoltaics (PVs) can deliver clean and cost-effective energy, the intermittent nature of the sunlight can lead to challenges with electric grid stability. Smart inverter-based resources (IBRs) can be used to mitigate the impact of such high penetration of renewable energy, as well as to support grid reliability by improving the voltage and frequency stability with embedded control functions such as Volt-VAR, Volt–Watt, and Frequency–Watt. In this work, the results of an extensive experimental study of possible interactions between the unstable grid and two residential-scale inverters from different brands under different active and reactive power controls are presented. Two impedance circuits were installed between Power Hardware-in-the-loop (P-HIL) equipment to represent the impedance in an electric distribution line. Grid voltage and frequency were varied between extreme values outside of the normal range to test the response of the two inverters operating under different controls. The key findings highlighted that different inverters that have met the same requirements of IEEE 1547-2018 responded to grid instabilities differently. Therefore, commissioning tests to ensure inverter performance are crucial. In addition to the grid control, the residential PV installed capacity and physical distances between PV homes and the substation, which impacted the distribution wiring impedance which we characterized by the ratio of the reactive to real impedance (X/R), should be considered when assigning the grid-supporting control setpoints to smart inverters. A higher X/R of 3.5 allowed for more effective control to alleviate both voltage and frequency stability. The elimination of deadband in an aggressive Volt-VAR control also enhanced the ability to control voltage during extreme fluctuation. The analysis of sudden spikes in the grid responses to a large frequency drop showed that a shallow slope of 1.5 kW/Hz in the droop control resulted in a >65% lower sudden reactive power overshoot amplitude than a steeper slope of 2.8 kW/Hz.

This paper evaluates residential smart photovoltaic (PV) inverters’ responses to cyberattacks and assesses the performance of an intrusion detection strategy for smart grid devices by comparing time-series power flow results from a simulation application called Faster Than Real-Time (FTRT) Simulator to measurements from a Power Hardware-in-the-Loop (P-HIL) laboratory as a testbed. Twenty different cyberattacks from three classes - Denial of Service (DoS), Intermittent attack, and Modification - were designed and tested with grid-tied smart inverters in order to study the inverters’ responses to malicious activities. The intrusion detection strategy was developed using a comparison between the predicted PV power output from FTRT and the power flows measured from P-HIL laboratory through the API interface. Real and reactive power thresholds were assigned based on a number of repeated experiments to ensure the applicability of the thresholds. The results showed that inverters from different manufacturers have their own unique responses which could be detected by the power flow measurements. Our detection method could identify over 94% of actual malicious actions and 7.4% of no-attack hours are detected as false positives. Out of 38 under-attack hours, 2 undetected hours are due to the intermittent attacks. Different attacks can be detected based on the targeted components of the complex power that attackers are aiming to cause disturbances. Our findings additionally show that DoS can be noticed immediately after the devices have been sabotaged, and they can be detected from the active power analysis. However, modification attack detection will depend more on the reactive power measurements, while intermittent attacks remain the most challenging for the proposed detection method since the objective of intermittent attacks is to create an oscillation of the complex power components which need a relatively high time resolution for the measurement.

The exponential growth of Photovoltaic (PV) technology is creating concerns for electric grid operators. As PV penetration increases, overvoltage in the distribution network can occur due to a mismatch between PV generation and load demand. However, PV smart inverters can be part of the solution to stabilize grid voltage. By providing reactive power and other grid supporting functions, PV inverters in a distribution network can mitigate this problem and enable a higher integration of renewable energy. To accomplish this, characterization and testing of advanced functions must be performed at a small scale before deploying these strategies in a field. In this work, we described in detail the components and communication interfaces of a Hardware-in-the-Loop testbed that includes two 3.8 kW PV inverters from different manufacturers. We conducted efficiency tests on the inverters and characterized the grid supporting functions for grid voltage stabilization, specifically constant power factor, volt-var, and volt-watt. We identified some abnormalities in the operation of the volt-var-watt control in one of the inverters and presented a method to overcome the limitation in remote control of another inverter using Modbus communication. Identifying, understanding, and overcoming shortcomings on the operation of PV smart inverters that provide grid supporting functions is key for the quick adoption of this technology and can help regulatory agencies to determine what is the appropriate control mode that will facilitate higher PV capacity. Additionally, we discuss the economic and technical implications of operating the inverter in active or reactive power grid control.

This paper studies the impacts of inverter clipping on bifacial PV modules under different weather and ground reflectivity. A 5 kW bifacial array was connected to a 3.8 kW grid-tied inverter, a 10 kWh Li-ion battery, and an EV charger. A PV output calculation model was developed to compare the estimated output of the modules with the actual measurements to evaluate the relation between ground reflectivity and clipping loss. The results showed that clipping potentially occurs on sunny days in summer from 10:00 to 15:00 during the period with the highest solar irradiance. Three colors of ground cover were also examined to compare the performance of bifacial modules under different albedo reflective properties. The results indicated that the white ground in winter leads to the highest bifacial gain (13.1%) and daily DC efficiency (22.2%) due to the combination of high reflectivity with low solar angle giving maximum upward reflection of direct sunlight. This same combination shows a minimal advantage in summer due to the clipping. The proposed model is evaluated, demonstrating 98.2% agreement between modeled and actual data for all conditions. Furthermore, simulation models based on the actual system with different system sizes and ground reflectivities have been studied to evaluate the impacts of the clipping in terms of technical losses and financial returns. The analysis shows that a high reflective ground condition can provide the best financial benefit, and the clipping loss does not have a great effect on the finance of the project since the loss is less than 4% of the annual production even in an extreme case.

Smart PV inverters will play a significant role in supporting the electric grid and mitigating the effect of high solar energy penetration. Since smart inverters provide communication capabilities with realtime grid control and monitoring, they could be vulnerable to cyberattacks. Understanding the responses of smart inverters to cyberattacks is essential for system operators and PV owners to protect the system from malicious attacks. In this work, we designed and demonstrated two intermittent cyberattacks on two smart PV inverters from different manufacturers to observe their responses in terms of real and reactive power output. The results show that different inverters have their unique response during and after the cyberattacks which need to be recovered using different methods.